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responses, offer suggestions and other thoughts for your colleagues to consider. 1, Responds to this post in half a page Compare and contrast the different types of metric tools (e.g., surveys, chart review, etc) that can be used to collect information. Include in your discussion the role of technology in metric tool selection and use (e.g., online survey software vs. paper and pencil collection). The various types of data collection metric tools are important because the systematic and analytical approach used by the researcher determines how information is collected and used (Paradis et al, 2016). Because research is conducted in a variety of ways for various purposes, metric tool selection is critical for data selection. The different types of data collection metric tools are questionnaires, interviews, Focus group discussions (FGDs) observations, surveys, chart review, among others (Kabir & Muhammad, 2016). Questionnaires- is the process of gathering information using an instrument and a system of asking a series of questions to elicit a response from a predetermined group (Form plus, 2020). Questionnaires can be distributed to many people while remaining cost-effective, simple to analyze, and safe for participants. However, some questions may go unanswered, and some answers may be deceptive. Observation- data can be obtained through observing an experience or an item. This approach is straightforward to administer and may be appropriate in some circumstances (Form plus 2020). They are great for exploring and comprehending activities, relationships, and taken-for-granted ways of doing things in the instant they occur (Paradis et al, 2016). However, bias may occur and may be costly to administer. Interviews- is a face-to-face interaction between two people with the primary objective of obtaining pertinent information for research purposes. Many study issues that may be addressed via surveys can also be addressed via interviews; however, interviews typically generate more detailed data than surveys (Paradis et al. 2016). They do, however, necessitate additional time and money for conducting and analyzing. Chart reviews/Medical Records- chart reviews compile information from a variety of private and public sources, including billing records, medical records, health surveys, and health plans. These evaluations offered factually accurate and fair information (Saczynski, McManus, Goldberg, 2013). The information is easily accessible and can be linked to additional follow-ups. However, data collection is not always thorough, and prior to usage, legal clearance must be acquired. Technology enables researchers to collect data in novel and creative ways. Several options must be considered when selecting a metric tool for data collection. For example, when comparing online survey data collection to paper and pencil data collection, technology has ensured that researchers focus on the interview rather than the complicated electronic filtering and routing (Ahmed, et al. 2018). Technology enables the implementation and application of more sophisticated research methods. Furthermore, when compared to paper-and-pencil data collection, using software technology provides timely, high-quality data with fewer inconsistencies and errors (Ahmed, et al. 2018). Briefly describe the importance of reliability and validity in relation to data collection and analysis of outcomes. Validity in research refers to a study’s ability to precisely answer the research question or the strength of the study’s conclusions. It refers to the degree to which the tool being evaluated accurately measures the primary result of interest. When an instrument produces the same results every time it is used in the same situation with the same types of subjects, it is said to be reliable (Sullivan, 2011). It is a component of the validity assessment. The reliability and validity of measurements are critical for the interpretation and generalizability of research findings. In data collection and analysis processes, emphasizing data reliability and validity has a significant impact. According to Cheliotis et al. (2015), validity and reliability ensure that research questions are accurately answered, resulting in the formulation of accurate and most effective policies to solve problems. They also aid in reducing resource waste caused by erroneous findings (Cheliotis et al. 2015). Twisted findings do not paint a clear picture of the actual events, leading to incorrect conclusions. Furthermore, analysis based on valid and reliable data prevents compromising decisions for public policy, which defeats the entire data collection process. What is the documented reliability (state the value) of the tool the clinicians selected for the project discussed in the case study? Based on this value what do you conclude about the tool? The documented reliability of the Self-efficacy for managing chronic disease 6-item scale is .91. The tool is a reliable and valid instrument to assess patients’ self?efficacy for managing chronic diseases Describe why it is necessary to code the collected data prior to statistical analysis. Provide an example of coding translation for one of the demographic data points listed in the case study. Coding is an important step in qualitative research. It entails disassembling qualitative data to examine the results and then reassembling the data in a meaningful manner (Elliot, 2018). It is a process of decision-making. Coding is a method of mapping data to provide an overview of the data and allow the researcher to make sense of the research questions. This is because text data is dense data, and it takes longer to sort through and make sense of it. Most importantly, researchers code to understand data, to spend time with it, and to eventually make sense of it so that they can report on it (Elliot, 2018). Codes are assigned to non-numerical data before it is brought to an Excel sheet because data must be numeric to perform certain functions in Excel. However, most numerical data, such as age, does not require coding. Determine the number of distinct response options for each variable first. Determine whether the response options are ordinal-level variables. This is due to their logical arrangement (Elliot, 2018). Furthermore, because Excel does not handle empty cells well, code even the missing values. Finally, enter the data for analysis. Here’s an example of coding a gender translation and the use of the internet for health information. Gender: Male = 1 while Female = 2, Use of Internet Information: 1 = yes while 2 = no. References Ahmed R, Robinson R, Elsony A, Thomson R, Squire SB, Malmborg R, et al. (2018) A comparison of smartphone and paper data-collection tools in the Burden of Obstructive Lung Disease (BOLD) study in Gezira state, Sudan. PLoS ONE 13(3): e0193917. Cheliotis, G., Lu, X., & Yi, S. (2015, April). Reliability of Data Collection Methods in Social Media Research. In Ninth International AAAI Conference on Web and Social Media. Elliott, V. (2018). Thinking about the coding process in qualitative data analysis. The Qualitative Report, 23(11), 2850-2861. Formplus (2020). Kabir, Syed Muhammad. (2016). METHODS OF DATA COLLECTION. Retrieved from < Paradis, E., O'Brien, B., Nimmon, L., Bandiera, G., & Martimianakis, M. A. (2016). Design: selection of data collection methods. Journal of Graduate Medical Education, 8(2), 263–264. Saczynski, J. S., McManus, D. D., & Goldberg, R. J. (2013). Commonly used data-collection approaches in clinical research. The American Journal of Medicine, 126(11), 946-950. Sullivan G. M. (2011). A primer on the validity of assessment instruments. Journal of Graduate Medical education, 3(2), 119–120. In your peer responses, offer suggestions and other thoughts for your colleagues to consider. 2, Responds to this post in half a page Compare and contrast the different types of metric tools (., surveys, chart review, etc) that can be used to collect information. Include in your discussion the role of technology in metric tool selection and use (., online survey software vs. paper and pencil collection). Several metric tools exist to collect accurate information; selecting an appropriate one may be challenging. According to Harris et al. (2020), interviews, chart reviews, surveys, run charts, and focus groups are various metric tools that fit projects and may be used as methods of portraying information about data and measurements. A survey is a clear and concise method of gathering information from a large group. A run chart is a valuable tool to track information, predict trends, evaluate data patterns and shifts. The run chart can predict common causes, variations, and data stability, comparing measures before and after implementing the process plan, assessing and revealing the randomness of patterns, variations, and consistency of the central tendency over time (Department of Health, .). A chart review is a relatively easy and less resource-intense manner to obtain retrospective data on particular clinical problems and answer specific clinical questions for current clinical issues (Sarkar & Seshadri, 2014). I might use chart review to obtain figures relating to the number of patients that were negatively affected by the clinical problem. Then, use a run chart to track information, predict trends during the project, monitor and evaluate the patterns of the practice change in the clinic and the community. Using information technology with computerized electronic health records software provides valuable tools for easy retrieval, usage, and dissemination of chart review and a Run chart documents versus manually accessed patients’ medical records for review compared to paper charts. • Briefly describe the importance of reliability and validity in relation to data collection and analysis of outcomes. Validity is the quality of the test measure being logical and accurate. It is the extent a testing tool measures what it claims to measure. Validity has to do with the method and accuracy of the data collection and testing instrument in producing results that correspond to real property (Salkind, 2022). Validity measures how well the results correspond to establishes theories, models, other measures of the same concept, and its applicability in real life. Reliability is the quality of the test in being consistent, stable, and reproducible if repeated in a similar situation and on different occasions (Salkind, 2022). Reliability pertains to the consistency of the result across different observers, parts of the test, and the ability to survive the test of time. A reliable test result focuses on the purpose of the problems, predictable aims, and hypothesis and is devoid of potential external variables. To ensure that accurate and reliable results are obtained, an attempt should be made to ensure that the instruments are standardized and precise across all settings where the test is administered (Salkind, 2022). • What is the documented reliability (state the value) of the tool the clinicians selected for the project discussed in the case study? Based on this value, what do you conclude about the tool? The documented tool used by the clinicians in the case study of self-efficacy for chronic disease management has an internal consistency measure of the reliability of .91 (Stanford/Garfield Kaiser chronic disease dissemination study, 2001). The possible scores of the scale range from 1-10, with the high score indicating self-efficacy (Kim & Youn, 2015). According to Salkind (2022), while a correlation of .70 is very strong, a .90 correlation value indicates an almost perfect correlation for test results. This implies that the clinicians' tool located through Stanford Patient Education Research Center and used for the case study is reliable. High consistency of the testing tool was reported, but that does not necessarily indicate that the result is valid; instead, the reverse is generally the case. • Describe why it is necessary to code the collected data prior to statistical analysis. Provide an example of coding translation for one of the demographic data points listed in the case study. Coding allows the reduction of extensive quantitative and qualitative data, organizing, categorizing, and transforming information into a suitable and useable computer-aided analysis (Linneberg & Korsgaard, 2019). Example coding patients’ information categorizes them into small groups such as of age (< 18, 18-27, 28-37, 38-47, 48-57, 58-67, >67), race (African American, Caucasian, Asian, Hispanics/Latino, American Indian, Japanese), gender (Male, Female), technology use (Never, Seldom, Always, Often), level of education (high school, some college, college, advance degree). This allows for easy organization, categorization, correlating, and analysis by the information technology. References Department of Health. (.). Run chart. Harris, J., Roussel, L., Dearman C., & Thomas, P. (2020). Project planning and management. A guide for nurses and interprofessional teams (3rd ed.). Jones & Barlett Learning, LLC. Kim, S., & Youn, C. (2015). Efficacy of chronic disease self-management program in older korean adults with low and high health literacy. Asian Nursing Research, 9(1), 42–46. Lineberg, M. S. & Korsgaard, S. (2019). Coding qualitative data: A synthesis guiding the novice. Qualitative Research Journal, 19(3), 259–270. Lorig, K. R., Sobel, D. S., Ritter, P. L., Laurent, D., Hobbs, M. (2001). Effect of a self- management program on patients with chronic disease. Effective Clinical Practice, 4, 256-262. Salkind, N. J. & Fry, B. B. (2022). Statistics for people who (think they) hate statistics. Using Microsoft Excel 2022. (5th ed.). Sage Publications. Sarkar, S., & Seshadri, D. (2014). Conducting record review studies in clinical practice. Journal of clinical and diagnostic research: JCDR, 8(9